Qwen 3.5 27B
Qwen develops the Qwen 3.5 27B FP 8, a chat model exceling at tasks such as reasoning, coding, and visual understanding, thanks to its unified vision-language foundation and efficient hybrid architecture. With a context window of 262,144 tokens, this model is capable of handling extensive inputs, including text and images.
Input
Output
Context
262K
Max Output
66K
Parameters
27.8B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Served variants
The same model in other encodings or serving configurations. Requesting qwen3-5-27b lets routing pick among them; the ids below pin one build.
qwen3-5-27b:fp8quantized
Benchmarks
Resources & Links
Estimated GPU requirements for Qwen 3.5 27B
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Qwen 3.5 27B
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Qwen 3.5 27B advertises a context window of 262,144 tokens, with a maximum output of 66,000 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Qwen 3.5 27B is an open-weight model released under the Apache 2.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Qwen 3.5 27B accepts Text and Image and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
Qwen 3.5 27B has published results from Artificial Analysis, shown by suite in the benchmarks card above exactly as the publisher reported them. Scores are not combined across suites, and a suite that has not measured Qwen 3.5 27B is shown as not available rather than estimated.
Yes. Qwen 3.5 27B is served on the managed pool through the OpenAI-compatible endpoint as qwen3-5-27b, pinned by name or chosen by routing when it is the best fit for a request. The Try in Playground button opens it directly.
About 27.4 GB at INT8 for the weights and a default context, from the catalog's 27.8B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Sep 22, 2026
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